17 citations · 56 across the 13 of their papers we have counts for
17 papers
ViTALiTy: Unifying Low-rank and Sparse Approximation for Vision Transformer Acceleration with a Linear Taylor Attention
Jyotikrishna Dass, Shang Wu, Huihong Shi +4
Vision Transformer (ViT) has emerged as a competitive alternative to convolutional neural networks for various computer vision applications. Specifically, ViT multi-head attention…
BNS-GCN: Efficient Full-Graph Training of Graph Convolutional Networks with Partition-Parallelism and Random Boundary Node Sampling
Cheng Wan, Youjie Li, Ang Li +2
Graph Convolutional Networks (GCNs) have emerged as the state-of-the-art method for graph-based learning tasks. However, training GCNs at scale is still challenging, hindering both…
PipeGCN: Efficient Full-Graph Training of Graph Convolutional Networks with Pipelined Feature Communication
Cheng Wan, Youjie Li, Cameron R. Wolfe +3
Graph Convolutional Networks (GCNs) is the state-of-the-art method for learning graph-structured data, and training large-scale GCNs requires distributed training across multiple a…
LDP: Learnable Dynamic Precision for Efficient Deep Neural Network Training and Inference
Zhongzhi Yu, Yonggan Fu, Shang Wu +3
Low precision deep neural network (DNN) training is one of the most effective techniques for boosting DNNs' training efficiency, as it trims down the training cost from the finest…
I-GCN: A Graph Convolutional Network Accelerator with Runtime Locality Enhancement through Islandization
Tong Geng, Chunshu Wu, Yongan Zhang +6
Graph Convolutional Networks (GCNs) have drawn tremendous attention in the past three years. Compared with other deep learning modalities, high-performance hardware acceleration of…
RT-RCG: Neural Network and Accelerator Search Towards Effective and Real-time ECG Reconstruction from Intracardiac Electrograms
Yongan Zhang, Anton Banta, Yonggan Fu +6
There exists a gap in terms of the signals provided by pacemakers (i.e., intracardiac electrogram (EGM)) and the signals doctors use (i.e., 12-lead electrocardiogram (ECG)) to diag…